Britney Muller’s “The Hidden Side of AI” at MozCon : A Detailed Recap

The year is , and the annual MozCon just wrapped up. This year’s event was particularly buzzworthy, especially Britney Muller’s presentation. As the founder of Data Sci , Muller knows her stuff, and her talk, “The Hidden Side of AI: What Marketers Need to Know,” had everyone taking notes like crazy.

Muller’s presentation dove deep into the wild world of AI in digital marketing, covering everything from the ethical stuff to the practical applications and even what AI just can’t do (yet!). It was basically a crash course in how to use AI without accidentally unleashing a robot uprising, all delivered with Muller’s signature wit and clarity.

The Emergence of Generative AI

Muller kicked things off by breaking down the rise of generative AI. She talked about how it all started, this merging of AI, machine learning, deep learning, and natural language processing (NLP). It’s like AI’s own little superhero team-up! And according to Muller, generative AI’s superpowers come from this unique blend of technologies.

Imagine AI as this incredible tool that can create text, images, even music! It’s kinda mind-blowing, but as Muller pointed out, it’s important to remember that generative AI is only as good as the data it’s trained on.

The Crucial Role of Training Data

This is where things get really interesting (and maybe a little scary). Muller stressed how important training data is for AI models. She said AI doesn’t just reflect its training data—it’s like it puts it under a microscope and magnifies it.

And here comes the “hidden side” part. Muller got real about bias in datasets. She used Wikipedia as an example. Since most Wikipedia contributors are male, the AI models trained on that data might have some, shall we say, “interesting” biases.

Practical Applications and Limitations of AI in Marketing

What Generative AI Excels At:

Okay, so we’ve covered the philosophical stuff, but what about the actual, you know, using AI for marketing stuff? Muller didn’t disappoint! She showed off a ton of practical applications for AI that had the audience nodding along. Think sentiment analysis (figuring out if people love or hate your brand online), categorization and labeling (so you don’t have to do it manually!), and even code support (because who hasn’t needed a little coding help?).

But here’s the kicker: Muller actually argued that content generation, which everyone’s always raving about, is kinda weak sauce when it comes to LLMs. Yep, you read that right! She basically said that while AI can write a decent blog post, it’s not going to win any Pulitzer Prizes anytime soon.

Specific GenAI SEO/Marketing Applications:

But even if AI isn’t churning out award-winning novels yet, it’s still pretty darn good at some specific SEO and marketing tasks. Muller gave us a whole laundry list of examples, like:

• Automatic title and meta description generation: Say goodbye to writer’s block for those tiny but mighty snippets of text.
• Data cleaning: Because nobody likes sifting through messy spreadsheets.
• Code assistance: For when you need to wrangle some HTML or JavaScript but don’t want to pull an all-nighter.
• Accelerating creativity and ideation: Think of AI as your brainstorming buddy, always ready with a fresh idea.
• Personalized outreach: Make those cold emails a little less…cold.
• Sentiment analysis: Figure out if people are digging your new product launch or not.
• Content refurbishment: Breathe new life into old blog posts and articles.
• Chatbots: Provide instant customer service, even if you’re on a beach somewhere sipping a margarita.
• Meeting note transcription: No more frantically scribbling notes while your boss is talking!

What Generative AI Struggles With:

Of course, even the smartest AI has its limits. Muller didn’t shy away from talking about the things GenAI just isn’t good at—yet. Here are a few areas where LLMs still need some work:

• Factual accuracy: AI can sometimes make stuff up, which is not ideal if you’re trying to be, you know, accurate.
• Common sense reasoning: You know that thing humans do where we understand the context and unspoken rules of a situation? Yeah, AI is still working on that.
• Contextual understanding: This ties into common sense reasoning. AI can struggle to understand the nuances of language and situations.
• Handling uncommon scenarios: Throw a curveball at an AI, and it might just strike out.
• Emotional intelligence: AI can analyze sentiment, but it can’t truly understand or replicate human emotions (yet!).
• Math and counting: Surprisingly, the things we learn in elementary school can trip up even the most advanced AI.

Muller’s point? Marketers need to be aware of both the strengths and weaknesses of AI. Don’t expect it to solve all your problems overnight, but don’t be afraid to experiment and see what it can do.

Prompt Engineering Tips

Speaking of experimenting, Muller gave the audience some killer tips on how to get the most out of generative AI. It’s all about something called “prompt engineering,” which basically means talking to AI in a way it understands.

Here are Muller’s golden rules of prompt engineering:

1. Explain the task clearly: Pretend you’re talking to a (very literal) human. Break down the task into simple steps.
2. Provide examples: Show, don’t tell! Giving AI examples of what you want is like giving it a cheat sheet.
3. Assign a “role” to the model and specify the intended audience: Want AI to write a blog post? Tell it to “act as a blogger” writing for “[your target audience]”.

Muller especially emphasized the power of examples. Research shows that giving AI examples in your prompts can drastically improve the quality of its output. So, don’t be shy—give those AIs all the examples they can handle!

Generative AI Tools and Resources

Of course, no MozCon presentation would be complete without a little something extra. Muller hooked the audience up with a list of tools and resources to get them started with generative AI:

• Colab: For all your Python coding needs.
• Kaggle: A playground for data scientists and AI enthusiasts.
• GPT for Sheets: Integrate the power of GPT directly into your spreadsheets.
• Ollama: A powerful open-source large language model.
• WordCrafter.ai: Because sometimes you just need help finding the right words.
• DataSci101.com: Muller’s own website, packed with resources and tutorials.

Key Takeaways and the Future of AI in Marketing

As Muller wrapped up her presentation, she left the audience with some key takeaways. Her main message? AI is a powerful tool, but it’s just that—a tool. It’s up to humans to use it ethically and effectively.

Here are Muller’s parting words of wisdom:

• Generative AI is a predictive technology: It’s really good at making predictions based on data, but it’s not psychic (yet!).
• A model’s quality is directly linked to its training data: Garbage in, garbage out, as they say.
• Marketers have the power to develop innovative GenAI applications: The future of AI is in our hands, folks!
• Engage in online conversations relevant to your product/service: This is where you can really understand what your audience cares about.

Muller also reminded everyone that AI should be seen as an assistive technology, not a replacement for human expertise. In other words, AI can help us do our jobs better and faster, but it can’t replace the human touch.

Call to Action

Muller wasn’t content to just drop some knowledge bombs and walk away. She gave the audience a clear call to action, urging them to:

• Uphold ethical practices when using AI: Just because we can do something doesn’t mean we should.
• Prioritize human needs and consider AI’s impact: How will AI affect our jobs, our lives, and our society as a whole?
• Capitalize on AI’s strengths while acknowledging its weaknesses: Use AI strategically, and don’t be afraid to get your hands dirty.

Her final message was all about finding a balance. We can embrace the efficiency and power of AI while still maintaining the human touch that makes marketing meaningful.

Conclusion

Britney Muller’s “The Hidden Side of AI” was more than just a presentation—it was a wake-up call. She challenged the audience to think critically about the role of AI in marketing and to use this powerful technology ethically and effectively. The message was clear: The future of AI is up to all of us. Let’s make sure we build it right.